Patients Say ‘No Thanks’ To Risky Medical Treatments
A recent study suggests that increasing patient responsibility for making medical decisions may decrease their willingness to accept risky treatment options. Details of this proof-of-concept study appear in the December issue of Arthritis Care & Research, a journal published by Wiley-Blackwell on behalf of the American College of Rheumatology.
According to the Centers for Disease Control and Prevention (CDC) nearly 1.1 billion visits to physician offices and hospital outpatient and emergency departments were made in the U.S. in 2006. A noval approach to doctor-patient interactions has emerged where both a patient and health care professional share information and jointly decide on course of treatment for the patient. This approach called shared-decision making (SDM) has been used in clincical settings to improve the quality of care for patients. Past studies have shown that increasing patient participation in decision-making decreases utiliztion of risky procedures. Other studies indicate that risk perception is increased under conditions that emphasize choice.
Liana Fraenkel, M.D., M.P.H., from Yale University School of Medicine and Ellen Peters, Ph.D., from Decision Research enrolled 216 participants in their medical decision making study. A demographic profile of the subjects showed that 70% were Caucasian, 62% were female, and the mean age was 59 years. Participants attending outpatient clinic appointments were asked to view a video in which a physician described the availability of a new medication associated with a rare risk of a serious side effect. (more…)
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Digital Communication Technology Could Lead to Individualized Medical Treatments
Researchers at the Burnham Institute for Medical Research (Burnham) have shown that search algorithms used in digital communications can help scientists identify effective multi-drug combinations. The study, led by Giovanni Paternostro, M.D., Ph.D., was published in the December 26, 2008, issue of PLoS Computational Biology.
Using the stack sequential algorithm, which was developed for digital communications, the team of scientists searched for optimal drug combinations. This algorithm can integrate information from different sources, including biological measurements and model simulations. This differs from the classic systems biology approach by having search algorithms rather than explicit quantitative models as the central element. The variability of biological systems is the fundamental motivation for this strategy. (more…)
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